1. Field of the Invention
The present invention generally relates to inventory management and, more particularly, to a value-based framework for inventory management that enables companies to calculate optimal inventory quantities using financial tools usually used to manage a portfolio of financial instruments.
2. Background Description
Inventory management is a well-established discipline both in the academic and business world. The methodologies and techniques are also well known. The common objective of widely used methods is typically to minimize inventory related costs or achieve a pre-specified customer serviceability target within a budget. It can also be profit or revenue maximization. In general, one can classify inventory management problems into two categories: deterministic demand, and stochastic demand. In both categories there are well known models that have been developed over the years. For instance, the method of MRP (Material Requirements Planning) is an example of deterministic inventory planning. MRP is used in relatively more complicated manufacturing and distribution systems and therefore, in order to simplify the planning process, future demand is typically assumed to be a known quantity. An example to the second category is the (S,s) inventory model where an order of Q=S−s is placed when inventory position (inventory on hand+on order−demand backlogs) drops to s. Optimality of (S,s) policies were proven by Herbert Scarf in “The Optimality of (s,S) Policies in the Dynamic Inventory Problem”, Mathematical Methods in the Social Sciences, (Ed.), Arrow, Karlin, Suppes, Stanford University Press, (1959), pp. 196-202, and later by D. L. Iglehart in “The Dynamic Inventory Problem with Unknown Distributions of Demand”, Management Science, 10, (1964), pp. 429-440, under more general conditions. Since then, (S,s) policies have received a lot of attention from researchers in both industry and academia. Practical implementation of (S,s) policies are facilitated by R. Ehrhardt in “The Power Approximation for Computing (S,s) Inventory Policies”, Management Science, 25, (1979), pp. 777-786, and more recently by Y. S. Zheng and A. Federgruen in “Finding Optimal (s,S) Policies Is About as Simple as Evaluating a Single Policy”, Operations Research, 39, 4, (1992), pp. 654-665. A collection of inventory models in advanced distribution systems can be found in L. B. Schwartz, Multi-Level Production/Inventory Control Systems: Theory and Practice, North-Holland, Amsterdam, (1981). For a more focused analysis of single-product, single-facility inventory systems, see H. L. Lee and S. Nahmias, “Single-Product, Single-Location Models”, Logistics of Production and Inventory, Handbooks in Operations Research and Management Science, S. C. Graves, H. G. Rinnooy Kan, and P. H. Zipkin (Eds.), vol. 4, North-Holland, Amsterdam, (1993).
Well established inventory replenishment methods such as the (S,s) inventory model are widely used across industries, most typically for retail, wholesale and manufacturing environments. The general focus of these methods is to calculate optimal inventory levels so as to meet customer serviceability objectives and/or financial objectives such as maximizing profit or revenue or minimizing cost. or revenue or minimizing cost.
Inventory management is perceived to be a different problem than financial risk management in company practice today. However, one can draw a parallel between inventory management and asset portfolio management and, using this parallel, one can put inventory management into a financial management perspective.